Search Results for "framework python" - Page 22
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Showing 1749 open source projects for "framework python"
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AutoResearchClaw
Autonomous research from idea to paper. Chat an Idea. Get a Paper 🦞
AutoResearchClaw is an open-source framework designed to automatically generate full academic research papers from a single idea or topic. Built in Python, it orchestrates a multi-stage research pipeline that gathers literature, formulates hypotheses, runs experiments, analyzes results, and writes the final paper. The system retrieves real academic references from sources such as arXiv and Semantic Scholar to ensure credible citations. -
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Watermark Anything
Official implementation of Watermark Anything with Localized Messages
Watermark Anything (WAM) is an advanced deep learning framework for embedding and detecting localized watermarks in digital images. Developed by Facebook Research, it provides a robust, flexible system that allows users to insert one or multiple watermarks within selected image regions while maintaining visual quality and recoverability. Unlike traditional watermarking methods that rely on uniform embedding, WAM supports spatially localized watermarks, enabling targeted protection of... -
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SlowFast
Video understanding codebase from FAIR for reproducing video models
SlowFast is a video understanding framework that captures both spatial semantics and temporal dynamics efficiently by processing video frames at two different temporal resolutions. The slow pathway encodes semantic context by sampling frames sparsely, while the fast pathway captures motion and fine temporal cues by operating on densely sampled frames with fewer channels. Together, these two pathways complement each other, allowing the network to model both appearance and motion without... -
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Qwen-Agent
Agent framework and applications built upon Qwen>=3.0
Qwen-Agent is a framework for building applications / agents using Qwen models (version 3.0+). It provides components for instruction following, tool usage (function calling), planning, memory, RAG (retrieval augmented generation), code interpreter, etc. It ships with example applications (Browser Assistant, Code Interpreter, Custom Assistant), supports GUI front-ends, backends, server setups. Agent workflow can maintain context / memory to perform multi-turn or more complex logic over time.... -
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H2O LLM Studio
Framework and no-code GUI for fine-tuning LLMs
Welcome to H2O LLM Studio, a framework and no-code GUI designed for fine-tuning state-of-the-art large language models (LLMs). You can also use H2O LLM Studio with the command line interface (CLI) and specify the configuration file that contains all the experiment parameters. To finetune using H2O LLM Studio with CLI, activate the pipenv environment by running make shell. With H2O LLM Studio, training your large language model is easy and intuitive. First, upload your dataset and then start... -
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Pacu
The AWS exploitation framework, designed for testing security
Pacu (named after a type of Piranha in the Amazon) is a comprehensive AWS security-testing toolkit designed for offensive security practitioners. While several AWS security scanners currently serve as the proverbial “Nessus” of the cloud, Pacu is designed to be the Metasploit equivalent. Written in Python 3 with a modular architecture, Pacu has tools for every step of the pen testing process, covering the full cyber kill chain. Pacu is the aggregation of all of the exploitation experience... -
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Prometheus-Eval
Evaluate your LLM's response with Prometheus and GPT4
...The repository includes a Python package that provides a straightforward interface for running evaluations and integrating them into model development pipelines. It also provides training data and utilities for fine-tuning evaluator models so they can assess outputs according to custom scoring rubrics such as helpfulness, accuracy, or style. -
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Chat with LLMs Everywhere
Run PyTorch LLMs locally on servers, desktop and mobile
TorchChat is an open-source project from the PyTorch ecosystem designed to demonstrate how large language models can be executed efficiently across different computing environments. The project provides a compact codebase that illustrates how to run conversational AI systems using PyTorch models on laptops, servers, and mobile devices. It is intended primarily as a reference implementation that shows developers how to integrate large language models into applications without requiring a... -
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RenderCV
LaTeX CV generator from a YAML/JSON input file
RenderCV is a LaTeX CV/resume framework. It allows you to create a high-quality CV as a PDF from a YAML file with full Markdown syntax support and complete control over the LaTeX code. RenderCV offers built-in LaTeX and Markdown templates ready to produce high-quality CVs. However, the templates are entirely arbitrary and can easily be updated to leverage RenderCV's capabilities with your custom CV themes. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Agent Lightning
The absolute trainer to light up AI agents
Agent Lightning is an open-source framework developed by Microsoft to train and optimize AI agents using techniques like reinforcement learning (RL), supervised fine-tuning, and automatic prompt optimization, with minimal or zero changes to existing agent code. It’s designed to be compatible with a wide range of agent architectures and frameworks — from LangChain and OpenAI Agent SDKs to AutoGen and custom Python agents — making it broadly applicable across different agent tooling ecosystems. ... -
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Wanwu AI Agent Platform
Enterprise AI agent platform for workflows, models, and RAG apps
Wanwu is an enterprise-grade AI agent development platform designed to help organizations build and deploy intelligent applications at scale. It provides a multi-tenant environment that enables teams to create AI agents, orchestrate workflows, and implement retrieval-augmented generation systems within a unified framework. Wanwu integrates large language models with business process automation, allowing developers to design complex, production-ready AI solutions tailored to enterprise needs.... -
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FinGPT
Open-Source Financial Large Language Models
FinGPT is an open-source, finance-specialized large language model framework that blends the capabilities of general LLMs with real-time financial data feeds, domain-specific knowledge bases, and task-oriented agents to support market analysis, research automation, and decision support. It extends traditional GPT-style models by connecting them to live or historical financial datasets, news APIs, and economic indicators so that outputs are grounded in relevant and recent market conditions... -
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Animated Drawings
Code to accompany "A Method for Animating Children's Drawings"
AnimatedDrawings is a framework that converts user sketches or line drawings into fully animated 2D motion sequences using learned motion priors. The idea is that you draw a simple static figure (stick figure, silhouette, or contour lines), and the system produces plausible skeletal motion (walking, jumping, dancing) that adheres to the drawn shape constraints. The architecture separates shape embedding (to understand user-drawn geometry) from motion embedding / generation (to produce... -
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AI Marketing Skills
Open-source AI marketing skills for Claude Code
AI Marketing Skills is a comprehensive open-source framework designed to transform AI agents into fully operational marketing and sales systems by equipping them with structured, reusable “skills” that automate real business workflows. Instead of simple prompts, the project provides complete operational modules that include scripts, scoring systems, and decision-making logic, allowing AI tools like Claude Code to execute complex marketing tasks end-to-end. The system is organized into... -
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Janus
Unified Multimodal Understanding and Generation Models
Janus is a sophisticated open-source project from DeepSeek AI that aims to unify both visual understanding and image generation in a single model architecture. Rather than having separate systems for “look and describe” and “prompt and generate”, Janus uses an autoregressive transformer framework with a decoupled visual encoder—allowing it to ingest images for comprehension and to produce images from text prompts with shared internal representations. The design tackles long-standing... -
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ddia
Designing Data-Intensive Application
ddia is a Chinese translation and online reading project for “Designing Data-Intensive Applications.” It covers both the first edition and ongoing second-edition translation work. The repository organizes the book content into chapters about data systems, storage, encoding, replication, partitioning, transactions, distributed systems, consistency, and derived data. It is built for readers who want deep systems design material in Chinese with a structured web reading experience. The project... -
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ContextGem
ContextGem: Effortless LLM extraction from documents
ContextGem is an open-source framework designed to simplify the extraction of structured data and insights from documents using large language models (LLMs). It provides a flexible, intuitive API that minimizes boilerplate code, enabling developers to build complex extraction workflows efficiently. ContextGem supports various document formats and integrates with multiple LLM providers, making it a versatile tool for tasks like contract analysis, anomaly detection, and information retrieval. -
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EvoTorch
Advanced evolutionary computation library built on top of PyTorch
EvoTorch is an evolutionary optimization framework built on top of PyTorch, developed by NNAISENSE. It is designed for large-scale optimization problems, particularly those that require evolutionary algorithms rather than gradient-based methods. -
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SkyPilot
SkyPilot: Run AI and batch jobs on any infra
SkyPilot is a framework for running AI and batch workloads on any infra, offering unified execution, high cost savings, and high GPU availability. Run AI and batch jobs on any infra (Kubernetes or 12+ clouds). Get unified execution, cost savings, and high GPU availability via a simple interface. -
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vyper
Pythonic Smart Contract Language for the EVM
See Installing Vyper to install vyper. See Tools and Resources for an additional list of framework and tools with vyper support. See Documentation for the documentation and overall design goals of the Vyper language. See Learn.Vyperlang.org for learning Vyper by building a Pokémon game. See try.vyperlang.org to use Vyper in a hosted jupyter environment! There is also an online compiler available you can use to experiment with the language and compile to bytecode and/or IR. While the vyper... -
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JoyAI-Echo
Pushing the Frontier of Long Audio-Visual Generation
JoyAI-Echo is an inference-focused framework for long-form audio-video generation. It is designed to create minute-level, multi-shot video stories from structured prompts while preserving continuity across scenes. The system uses a paired cross-modal memory bank to maintain visual identity and voice consistency over longer sequences. It also uses a distilled DMD generator to reduce inference cost and improve generation speed compared with heavier multi-step pipelines. JoyAI-Echo focuses on... -
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Agent Control
Centralized agent control plane for governing runtime agent behavior
Agent Control is a centralized control plane for governing AI agent behavior at runtime across different frameworks and deployment environments. It lets teams define controls once and apply them consistently to agents without rewriting the agent’s core code. The platform evaluates agent inputs and outputs against configurable policies to reduce risks such as prompt injection, unsafe responses, sensitive data exposure, and policy drift. It is designed for production environments where... -
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AWorld
Build, evaluate and train General Multi-Agent Assistance with ease
AWorld (Agent World) is an agent runtime/framework. It supports building, evaluating, and training self-improving intelligent agents and multi-agent systems (MAS). It is designed to provide infrastructure for agent orchestration, iterative learning, and environment interaction at scale. Scalable training across environments and distributed setups. Support for multi-agent collaboration/orchestration (MAS). The system is intended to help agents evolve via experience. It provides features to... -
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MLRun
Machine Learning automation and tracking
MLRun is an open MLOps framework for quickly building and managing continuous ML and generative AI applications across their lifecycle. MLRun integrates into your development and CI/CD environment and automates the delivery of production data, ML pipelines, and online applications, significantly reducing engineering efforts, time to production, and computation resources. MLRun breaks the silos between data, ML, software, and DevOps/MLOps teams, enabling collaboration and fast continuous... -
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RecursiveMAS
Offical Implementation for "Recursive Multi-Agent Systems"
RecursiveMAS is an advanced multi-agent AI framework that introduces a recursive collaboration mechanism to improve reasoning and problem-solving across multiple agents. Instead of treating agents as independent units exchanging text outputs, it connects them through a shared latent computation loop, allowing internal “thought states” to be passed and refined iteratively. This recursive structure enables agents to build on each other’s intermediate reasoning, leading to deeper and more...
